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Jambura Journal of Mathematics

jjom
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Published by Universitas Negeri Gorontalo

ISSN : 26545616 EISSN : 26561344 DOI : https://doi.org/10.34312/jjom

Core Subject : Education,

Mathematics

Jambura Journal of Mathematics (JJoM) is a peer-reviewed journal published by Department of Mathematics, State University of Gorontalo. This journal is available in print and online and highly respects the publication ethic and avoids any type of plagiarism. JJoM is intended as a communication forum for mathematicians and other scientists from many practitioners who use mathematics in research. The scope of the articles published in this journal deal with a broad range of topics, including: Mathematics; Applied Mathematics; Statistics; Applied Statistics.

Arjuna Subject : -

Articles 179 Documents

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An Exact Solution for a Single Machine Scheduling Under Uncertainty Rebaz Abdulla Sharif; Ayad M. Ramadan
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Here we have n jobs on one machine where the processing times are triangular fuzzy numbers. The jobs are available to process without interruption. The purpose is to find a best sequence of the jobs that minimizes total fuzzy completion times and maximum fuzzy tardiness. In this paper a new definition is presented called D-strongly positive fuzzy number, then an exact solution of the problem through this definition is found. This definition opens new ideas about converting scheduling problems into fuzzy cases.

Surjektifitas Pemetaan Eksponensial untuk Grup Lie Heisenberg yang Diperumum Edi Kurniadi; Putri Giza Maharani; Alit Kartiwa
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

The Heisenberg Lie Group is the most frequently used model for studying the representation theory of Lie groups. This Lie group is modular-noncompact and its Lie algebra is nilpotent. The elements of Heisenberg Lie group and algebra can be expressed in the form of matrices of size 3×3. Another specialty is also inherited by its three-dimensional Lie algebra and is called the Lie Heisenberg algebra. The Heisenberg Lie Group whose Lie Algebra is extended to the dimension 2n+1 is called the generalized Heisenberg Lie group and it is denoted by H whose Lie algebra is h_n. In this study, the surjectiveness of exponential mapping for H was studied with respect to h_n=⟨x ̅,y ̅,z ̅⟩ whose Lie bracket is given by [X_i,Y_i ]=Z. The purpose of this research is to prove the characterization of the Lie subgroup with respect to h_n. In this study, the results were obtained that if ⟨x ̅,y ̅ ⟩=:V⊆h_n a subspace and a set {e^(x_i ) e^(x_j ) ┤| x_i,x_j∈V }=:L⊆H then L=H and consequently Lie(L)≠V.

Robust Coloring Optimization Model on Electricity Circuit Problems Viona Prisyella Balqis; Diah Chaerani; Herlina Napitupulu
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

The Graph Coloring Problem (GCP) is assigning different colors to certain elements in a graph based on certain constraints and using a minimum number of colors. GCP can be drawn into optimization problems, namely the problem of minimizing the color used together with the uncertainty in using the color used, so it can be assumed that there is an uncertainty in the number of colored vertices. One of the mathematical optimization techniques in dealing with uncertainty is Robust Optimization (RO) combined with computational tools. This article describes a robust GCP using the Polyhedral Uncertainty Theorem and model validation for electrical circuit problems. The form of an electrical circuit color chart consists of corners (components) and edges (wires or conductors). The results obtained are up to 3 colors for the optimization model for graph coloring problems and up to 5 colors for robust optimization models for graph coloring problems. The results obtained with robust optimization show more colors because the results contain uncertainty. When RO GCP is applied to an electrical circuit, the model is used to place the electrical components in the correct path so that the electrical components do not collide with each other.

Value at Risk dan Tail Value at Risk dari Peubah Acak Besarnya Kerugian yang Menyebar Alpha Power Pareto Ruhiyat Ruhiyat; Berlian Setiawaty; Muwafiqo Zamzami Dhuha
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Value at Risk (VaR) and Tail Value at Risk (TVaR) are two measures that are commonly used to quantify the risk associated with a loss severity distribution. In this paper, both values are calculated analytically and estimated using a Monte Carlo simulation when the loss severity random variable has an alpha power Pareto distribution. This distribution is the result of alpha power transformation on a Pareto distribution. The random numbers used in the Monte Carlo simulation are generated from the alpha power Pareto distribution using the inverse transformation technique. In the special case used, the estimated VaR and TVaR values obtained from the Monte Carlo simulation for some security levels used are close to the actual VaR and TVaR values as long as the number of random numbers generated in the Monte Carlo simulation is sufficiently large.

On the Effects of Saturation Terms on A SEIR Epidemic Model with Infected and Susceptible Compartments Mutairu Kayode Kolawole; Olakunle L. Moshood; Kehinde A. Bashiru; Adedapo I. Alaje; Amos O. Popoola; Hammed O. Adekunle
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

The importance of the saturation term in an SEIR (Susceptible, Exposed, Infected, and Recovered) epidemic model was examined in this article. To estimate the basic reproduction number (R0), examine the stabilities and run numerical simulations on the model, the next generation matrix, the Lyapunov function and Runge-Kutta techniques were used. The numerical simulation results reveal that, the saturation term has a significant influence in the model’s susceptible and infected compartments. However, as demonstrated by the simulation results, saturation term has a greater influence on vulnerable people than on infected people. As a result, greater sensitization programs through seminars, media, and awareness will be more beneficial to the vulnerable class than the afflicted class during disease eradication.

Metode AdaBoost dan Random Forest untuk Prediksi Peserta JKN-KIS yang Menunggak Ikhlasul Amalia Rahmi; Farit Mochamad Afendi; Anang Kurnia
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

The contribution of participants, employers, and/or the government is one of the most important things in the National Health Insurance Program-Healthy Indonesia Card (JKN-KIS) implementation. All Indonesian residents were required to participate in the JKN-KIS program which is divided into four types of participation, one of which is Non-Wage Recipient Participants (PBPU) whose contributions are paid independently. However, based on December 2021 data, 60% of PBPU participants were late in paying monthly until they were in arrears. Arrears in payment of contributions cause several problems, including payment of claims to deficits. This research utilized big data owned by the Healthcare and Social Security Agency (BPJS Kesehatan) and machine learning based on ensemble trees, namely AdaBoost and random forest to get the predictions of participants in arrears. The results showed that machine learning based on an ensemble tree was able to predict PBPU participants in arrears with high accuracy, as evidenced by the AUC values in both models above 80%. The random forest model has an F1-score and the AUC value is better than the AdaBoost, namely the F1-score of 85,43% and the AUC value of 87,20% in predicting JKN-KIS participants who are in arrears in payment of contributions.

Pola Faktor Keragaman pada Respons Dikrit Fitri Nurjanah; Budi Suharjo; Hadi Sumarno
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

In social research, respondents are usually given several questions or indicators for assessment. Responses between respondents may differ even if the same questions or indicators are given. This is one of the causes of the diversity of responses. The diversity of responses is one of the factors that cause response bias in conducting social research. The diversity of responses can come from differences in the thought processes of each respondent. There are three main aspects in the thought process, namely cognition, affection, and conation. This paper aims to analyze the source of the diversity of responses in the aspects of cognition, affection, and conation. The first thing to do in this research is to design a questionnaire by developing indicators into three aspects (cognition, affection, and conation). The study involved 100 respondents using OVO with a purposive sampling method. Respondents assess indicators of aspects of cognition, affection, and conation. The assessment options given are discrete assessments 1-5 with a description of the assessment adjusted to the indicators. Then, the respondent's assessment data were analyzed by calculating the standard deviation, analysis of variance, further test (Tukey HSD) and the distribution of the assessment of each indicator. The main result obtained is that there are three consecutive indicators with the largest standard deviation values in each aspect. These indicators are the source of the diversity of responses in aspects of cognition, affection, and conation. The results of the analysis also show that the conation aspect is the most diverse aspect with the largest standard deviation value. This research is useful as a reference for making social research questionnaires in measuring aspects related to cognition, affection, and conation.

Analisis Performa Algoritma K-Nearest Neighbor dan Reduksi Dimensi Menggunakan Principal Component Analysis Aldila Dinanti; Joko Purwadi
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

This paper discusses the performance of the K-Nearest Neighbor Algorithm with dimension reduction using Principal Component Analysis (PCA) in the case of diabetes disease classification. A large number of variables and data on the diabetes dataset requires a relatively long computation time, so dimensional reduction is needed to speed up the computational process. The dimension reduction method used in this study is PCA. After dimension reduction is done, it is continued with classification using the K-Nearest Neighbor Algorithm. The results on diabetes case studies show that dimension reduction using PCA produces 3 main components of the 8 variables in the original data, namely PC1, PC2, and PC3. Then classification result using K-Nearest Neighbor shows that by choosing 3 closest neighbor parameters (K), for K = 3, K = 5, and K = 7. The result for K = 3 has an accuracy of 67,53%, for K = 5 had an accuracy is 72,72%, and for K=7 had an accuracy of 77,92%. Thus, it was concluded that the best accuracy performance for the classification of diabetes was achieved at K=7 with an accuracy of 77.92%.

Synthetic Minority Oversampling Technique Pada Model Logit dan Probit Status Pengangguran Terdidik Fatimah Fatimah; Anwar Fitrianto; Indahwati Indahwati; Erfiani Erfiani; Khusnia Nurul Khikmah
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i1.17050

Educated unemployment is caused by a misalignment of educational development planning and employment development, resulting in underemployed graduates from various educational institutions. Unemployment data in DKI Jakarta shows an unequal class. Unbalanced data is a severe problem of modeling because it can cause prediction errors that affect the accuracy of the resulting model. Using SMOTE to handle unbalanced data will likely increase the model’s accuracy. This study aims to find the best model for identifying the factors influencing the status of educated unemployment using logit and probit models and handling unbalanced data using SMOTE. The results showed that the independent variables that affect the status of educated unemployment in the logit and probit models are the same: age group and participation in training. The independent variables that affect the status of educated unemployment in the logit and probit models with SMOTE are also the same: age group, marital status, and participation in training. Unbalanced data handling using SMOTE can increase the balanced accuracy value significantly. Balanced accuracy values for the logit and probit models with SMOTE are higher than the logit and probit models without SMOTE. The logit model with SMOTE is the best because it has the highest balanced accuracy value compared to other models. According to the logit model with SMOTE, the educated unemployed in DKI Jakarta are young and have never married. There is a need for the government to play a role in improving the quality of educational institutions in producing graduates who meet company qualifications and can be hired by employers. Unemployed people who have attended the training, despite having a higher education, may also become unemployed. The training provided has not been able to reduce the unemployment rate. As a result, the government should be able to provide training to improve entrepreneurship skills while also providing capital in the form of business loans to reduce educated unemployment.

Model ETAS Spatio-Temporal pada Analisis Pemetaan Intensitas Kegempaan di Wilayah Sumatera Andreas Rony Wijaya
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

High seismic activity forces Indonesia to mitigate natural disasters to minimize the impact of these disasters. One of the mitigation efforts that can be done is to know the possibility of an earthquake occurring in an area. Earthquakes, which are random phenomena, cannot be determined with certainty. Therefore, studies in seismological statistics can be used. One of the studies in seismological statistics that discusses the occurrence of earthquakes is the epidemic-type aftershock sequence (ETAS) model. This model describes the main seismic activity followed by aftershocks. The ETAS model, which only considers the parameters of time and event magnitude, was developed into a Spatio-temporal ETAS model, which also describes spatial parameters or locations. This study used the Spatio-temporal ETAS model to analyze the Sumatra region’s seismic activity from 2000-2022. Earthquake data sources are obtained from the United State Geological Survey (USGS). Based on data analysis, the Spatio-temporal ETAS model expressed in terms of the conditional intensity function shows that earthquakes that occur in the Sumatera region with a large magnitude tend to produce a large conditional intensity function as well. The spatial component of the spatio-temporal ETAS model can be explained by mapping the peak ground acceleration (PGA). The results of the PGA mapping show that seismic activity in the Sumatera region is prone to occur along the north and west coasts of the Sumatra region, with PGA values ranging from 0.2 g to 0.9 g. The larger the PGA value means, the higher the risk of an earthquake occurring in the area marked with a reddish-yellow dot or contour.

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Resmawan

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info.jjom@ung.ac.d

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Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango, Gorontalo, Indonesia

Location
Kota gorontalo,

Gorontalo

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Resmawan

Contact Email resmawan@ung.ac.id

Phone +6285255230451

Journal Mail Official info.jjom@ung.ac.d

Editorial Address Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango, Gorontalo, Indonesia

Location Kota gorontalo, Gorontalo INDONESIA

Abstract

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Contact Name
Resmawan

Contact Email
resmawan@ung.ac.id

Phone
+6285255230451

Journal Mail Official
info.jjom@ung.ac.d

Editorial Address
Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango, Gorontalo, Indonesia

Location
Kota gorontalo,

Gorontalo

INDONESIA